Harshbarger Jayson, Kratz Anton, Carninci Piero
RIKEN Center for Life Science Technologies, RIKEN Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan.
BMC Genomics. 2017 Jan 7;18(1):47. doi: 10.1186/s12864-016-3396-5.
Differential gene expression (DGE) analysis is a technique to identify statistically significant differences in RNA abundance for genes or arbitrary features between different biological states. The result of a DGE test is typically further analyzed using statistical software, spreadsheets or custom ad hoc algorithms. We identified a need for a web-based system to share DGE statistical test results, and locate and identify genes in DGE statistical test results with a very low barrier of entry.
We have developed DEIVA, a free and open source, browser-based single page application (SPA) with a strong emphasis on being user friendly that enables locating and identifying single or multiple genes in an immediate, interactive, and intuitive manner. By design, DEIVA scales with very large numbers of users and datasets.
Compared to existing software, DEIVA offers a unique combination of design decisions that enable inspection and analysis of DGE statistical test results with an emphasis on ease of use.
差异基因表达(DGE)分析是一种用于识别不同生物学状态下基因或任意特征的RNA丰度中具有统计学显著差异的技术。DGE测试的结果通常使用统计软件、电子表格或自定义的临时算法进行进一步分析。我们发现需要一个基于网络的系统来共享DGE统计测试结果,并以非常低的入门门槛在DGE统计测试结果中定位和识别基因。
我们开发了DEIVA,这是一个免费的开源基于浏览器的单页应用程序(SPA),非常注重用户友好性,能够以即时、交互式和直观的方式定位和识别单个或多个基因。从设计上看,DEIVA能够适应大量用户和数据集。
与现有软件相比,DEIVA提供了独特的设计决策组合,能够以强调易用性的方式检查和分析DGE统计测试结果。